Multivariate Calibration and Model Integrity for Wood Chemistry Using Fourier Transform Infrared Spectroscopy
This research addressed a rapid method to monitor hardwood chemical composition by applying Fourier transform infrared (FT-IR) spectroscopy, with particular interest in model performance for interpretation and prediction. Partial least squares (PLS) and principal components regression (PCR) were cho...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-01-01
|
| Series: | Journal of Analytical Methods in Chemistry |
| Online Access: | http://dx.doi.org/10.1155/2015/429846 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849684982890496000 |
|---|---|
| author | Chengfeng Zhou Wei Jiang Qingzheng Cheng Brian K. Via |
| author_facet | Chengfeng Zhou Wei Jiang Qingzheng Cheng Brian K. Via |
| author_sort | Chengfeng Zhou |
| collection | DOAJ |
| description | This research addressed a rapid method to monitor hardwood chemical composition by applying Fourier transform infrared (FT-IR) spectroscopy, with particular interest in model performance for interpretation and prediction. Partial least squares (PLS) and principal components regression (PCR) were chosen as the primary models for comparison. Standard laboratory chemistry methods were employed on a mixed genus/species hardwood sample set to collect the original data. PLS was found to provide better predictive capability while PCR exhibited a more precise estimate of loading peaks and suggests that PCR is better for model interpretation of key underlying functional groups. Specifically, when PCR was utilized, an error in peak loading of ±15 cm−1 from the true mean was quantified. Application of the first derivative appeared to assist in improving both PCR and PLS loading precision. Research results identified the wavenumbers important in the prediction of extractives, lignin, cellulose, and hemicellulose and further demonstrated the utility in FT-IR for rapid monitoring of wood chemistry. |
| format | Article |
| id | doaj-art-bc47cce155b5478dbac53eed982bc416 |
| institution | DOAJ |
| issn | 2090-8865 2090-8873 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Analytical Methods in Chemistry |
| spelling | doaj-art-bc47cce155b5478dbac53eed982bc4162025-08-20T03:23:18ZengWileyJournal of Analytical Methods in Chemistry2090-88652090-88732015-01-01201510.1155/2015/429846429846Multivariate Calibration and Model Integrity for Wood Chemistry Using Fourier Transform Infrared SpectroscopyChengfeng Zhou0Wei Jiang1Qingzheng Cheng2Brian K. Via3Forest Products Development Center, School of Forestry and Wildlife Sciences, Auburn University, 520 Devall Drive, Auburn, AL 36849, USAForest Products Development Center, School of Forestry and Wildlife Sciences, Auburn University, 520 Devall Drive, Auburn, AL 36849, USAForest Products Development Center, School of Forestry and Wildlife Sciences, Auburn University, 520 Devall Drive, Auburn, AL 36849, USAForest Products Development Center, School of Forestry and Wildlife Sciences, Auburn University, 520 Devall Drive, Auburn, AL 36849, USAThis research addressed a rapid method to monitor hardwood chemical composition by applying Fourier transform infrared (FT-IR) spectroscopy, with particular interest in model performance for interpretation and prediction. Partial least squares (PLS) and principal components regression (PCR) were chosen as the primary models for comparison. Standard laboratory chemistry methods were employed on a mixed genus/species hardwood sample set to collect the original data. PLS was found to provide better predictive capability while PCR exhibited a more precise estimate of loading peaks and suggests that PCR is better for model interpretation of key underlying functional groups. Specifically, when PCR was utilized, an error in peak loading of ±15 cm−1 from the true mean was quantified. Application of the first derivative appeared to assist in improving both PCR and PLS loading precision. Research results identified the wavenumbers important in the prediction of extractives, lignin, cellulose, and hemicellulose and further demonstrated the utility in FT-IR for rapid monitoring of wood chemistry.http://dx.doi.org/10.1155/2015/429846 |
| spellingShingle | Chengfeng Zhou Wei Jiang Qingzheng Cheng Brian K. Via Multivariate Calibration and Model Integrity for Wood Chemistry Using Fourier Transform Infrared Spectroscopy Journal of Analytical Methods in Chemistry |
| title | Multivariate Calibration and Model Integrity for Wood Chemistry Using Fourier Transform Infrared Spectroscopy |
| title_full | Multivariate Calibration and Model Integrity for Wood Chemistry Using Fourier Transform Infrared Spectroscopy |
| title_fullStr | Multivariate Calibration and Model Integrity for Wood Chemistry Using Fourier Transform Infrared Spectroscopy |
| title_full_unstemmed | Multivariate Calibration and Model Integrity for Wood Chemistry Using Fourier Transform Infrared Spectroscopy |
| title_short | Multivariate Calibration and Model Integrity for Wood Chemistry Using Fourier Transform Infrared Spectroscopy |
| title_sort | multivariate calibration and model integrity for wood chemistry using fourier transform infrared spectroscopy |
| url | http://dx.doi.org/10.1155/2015/429846 |
| work_keys_str_mv | AT chengfengzhou multivariatecalibrationandmodelintegrityforwoodchemistryusingfouriertransforminfraredspectroscopy AT weijiang multivariatecalibrationandmodelintegrityforwoodchemistryusingfouriertransforminfraredspectroscopy AT qingzhengcheng multivariatecalibrationandmodelintegrityforwoodchemistryusingfouriertransforminfraredspectroscopy AT briankvia multivariatecalibrationandmodelintegrityforwoodchemistryusingfouriertransforminfraredspectroscopy |